Check the product facts AI shoppers are told
Proofsource product data accuracy shows which of your products AI answers describe correctly and which have a wrong price or attribute. For ecommerce and Shopify teams, it adds a store feed check against your live site and shopping reports on brands, merchants, products, keywords and trigger rate, so you can fix the data engines repeat.
| Product | Field | AI says | Your data |
|---|---|---|---|
| Trail E-Bike 500 | Price | 449 (last season) | 399 (current) |
| City Helmet Pro | Sizes | S, M | S, M, L |
| Commuter Lock X | Weight | 2.1 kg | 1.6 kg |
| Kids Bell | In stock | No | Yes |
AI product data accuracy, in short
The facts, ready to quote.
- What it checks
- Product prices and attributes in AI answers against your own data
- Feed check
- Compares your store feed with what your site shows
- Shopping reports
- Brands, merchants, products, keywords, trigger rate, feed audit and capture
- Engines
- Up to 10 AI engines, from ChatGPT and Perplexity to Gemini, Copilot and Grok
- Who it is for
- Ecommerce managers, Shopify merchants and their agencies
- After a fix
- Later answers are checked again, and a product moves from wrong to accurate when engines pick up the change.
AI product data accuracy, explained
AI product data accuracy is how closely AI answers match the real facts of your products: price, size, materials, compatibility, stock and the other attributes a shopper uses to decide. When someone asks an AI assistant which trail e-bike to buy, the answer often quotes a price or a spec. If that number comes from an old feed, a reseller listing or a stale page, the shopper gets the wrong picture before they ever reach your store.
Wrong product data usually has a plain cause: a feed that disagrees with the site, a page that hides key attributes behind scripts, or an old listing that engines still cite. Fixing it means finding which products are wrong, which field is wrong, and where the bad value lives.
Proofsource checks product attributes in AI answers against your data and lists the products and fields that are off. It checks your store feed against your site so the two tell the same story, and its shopping reports show which brands, merchants and products appear for your keywords and how often a question triggers product results.
How it works
Check whether AI answers get your product prices and attributes right, whether your store feed matches your site, and how products show up in AI shopping answers.
Read your catalog
Proofsource reads your products from your site and store feed.
Check the feed
The store feed check compares each feed item with what the product page shows.
Ask the engines
Shopping questions run on every engine your plan covers and the answers are captured.
Compare attributes
Prices and attributes in the answers are checked against your data, product by product.
Fix the source
Correct the feed or the page, then watch the attribute turn accurate in later answers.
See it in the product
Screens from the Proofsource app, drawn with sample data for an example brand.
| Item | Feed | Site |
|---|---|---|
| Trail helmet, red | Out of stock | In stock |
| City bell | Brass | Steel |
| Rear rack | Fits 26 in | Fits 26 to 29 in |
| Kids bell, blue | Ships in 2 days | Ships in 5 days |
| Product | Trigger rate | Shown by |
|---|---|---|
| Trail helmet | 34% | ChatGPTPerplexity |
| City bell | 12% | ChatGPT |
| Commuter lock | 21% | Google AI Overviews |
| Rear rack | 9% | Perplexity |
Every capability, live today
3 shipped capabilities behind AI product data accuracy, each in the product now.
Product attribute accuracy
Checks the prices and attributes AI answers give for your products against your own data, and lists each wrong field by product.
Store feed check
Compares your store feed with your live site and lists the items where the two disagree.
Shopping reports
Reports on the brands, merchants, products and keywords in shopping answers, the trigger rate, a feed audit and captured answers.
Who it is for
Stop AI quoting an old price
Find the products where answers show an outdated price and fix the feed or page they come from.
Keep feed and site in sync
Run the feed check after catalog updates so engines and marketplaces read one set of facts.
See which products get shown
Use trigger rate and the products report to see which items appear for buying questions.
Why it matters
Right facts at the moment of choice
Shoppers see a price or spec in the answer before they visit, so it has to be right.
Field-level detail
You see the product and the field that is wrong, not a vague score.
One source of truth
The feed check keeps your feed and your pages telling the same story.
Proof the fix worked
Later answers show whether the corrected attribute reached the engines.
AI product data accuracy: Proofsource and other tools
AI shopping visibility is a growing area and several tools cover it well; here is how their public pages describe it next to Proofsource.
| Capability | Proofsource | Profound | Peec AI | AthenaHQ | Rankscale |
|---|---|---|---|---|---|
| Product visibility in AI shopping answers | YesBrands, merchants, products, keywords and trigger rate | YesTracks product visibility in ChatGPT Shopping down to SKU levelSource | YesProduct visibility, win rate, ratings, competitors and source URLsSource | YesProduct appearance rates versus competitorsSource | YesShopping items, sponsored placements and buybox winsSource |
| Product price and attribute accuracy | YesChecks answer attributes against your data, per product and field | Not listed | Not listed | RelatedAction Center improves product content for AI recommendationsSource | Not listed |
| Store feed against site check | YesLists feed items that disagree with the live page | Not listed | Not listed | Not listed | Not listed |
| Product data connections | YesReads your store feed and compares it with the live page | RelatedProduct information integrationSource | Not listed | RelatedListed integrationSource | Not listed |
Where each of them shines
Profound tracks ChatGPT Shopping visibility down to the SKU and connects product data sources like Salsify and Bazaarvoice. Compare in full
Peec's shopping analytics cover win rate, ratings and source URLs, with filters by chat type. Compare in full
AthenaHQ pairs shopping visibility with an Action Center that improves product content.
Rankscale reads shopping items and sponsored placements across several engines, including buybox wins.
Questions about AI product data accuracy
What does AI product data accuracy mean?
It means the prices, sizes, specs and other attributes AI answers give for your products match your real data. Proofsource checks this product by product and names the field that is wrong.
Which AI engines does it check?
Proofsource tracks up to 10 AI engines: ChatGPT, Perplexity, Claude, Google AI Overviews, Google AI Mode, Gemini, Microsoft Copilot, Grok, DeepSeek and Meta AI. Which run depends on your plan.
Where do wrong product facts come from?
Usually from a store feed that disagrees with the site, an outdated page, or a reseller listing that engines cite. The store feed check catches the first one directly.
What does the store feed check do?
It compares each item in your store feed with what the matching product page shows, and lists the items where price, stock or attributes disagree.
What is trigger rate?
Trigger rate is how often a question produces product results in the answer. It tells you which buying questions are shopping moments for your category.
How is this different from Profound or Peec shopping tracking?
Profound and Peec track how often products appear in AI shopping answers, and do it well. Proofsource also checks whether the attributes in those answers are correct and whether your feed matches your site, so you can fix the data behind the answer.
How do I know a fix worked?
After you correct the feed or page, later answers are checked again and the product moves from wrong to accurate when engines pick up the change.
Keep exploring
Try it on your own brand.
Proofsource is live: scan your brand and see AI product data accuracy at work with your own answers, competitors and sources.